Protein interactions with the plasma membrane mediate processes critical for cell viability such as migration and endocytosis, yet our understanding of how recruitment of key proteins correlates with their ability to sense or induce energetically unfavorable plasma membrane shapes remains limited. Simultaneous two-wavelength axial ratiometry (STAR) microscopy provides millisecond time resolution and nanometer axial resolution of protein dynamics at the basal plasma membrane. However, STAR microscopy requires extensive and time-consuming quantitative data processing to access axial (Δz) information. Therefore, addressing questions about the influence of biological and biophysical factors on the interaction between the plasma membrane and protein of interest remains challenging. Here, we overcome the limitations in STAR data processing and present dynamic reference STAR (DrSTAR): a user-friendly, automated, open-source MATLAB-based package. DrSTAR enables processing multiple experimental conditions and biological replicates, employs a novel local background referencing algorithm, and accelerates processing time to facilitate broad adaptation of STAR for studying nanometer axial changes in protein distribution.

Fluorescence lifetime imaging captures the spatial distribution of chemical species across cellular environments employing pulsed illumination confocal setups. However, quantitative interpretation of lifetime data continues to face critical challenges. For instance, fluorescent species with known in vitro excited-state lifetimes may split into multiple species with unique lifetimes when introduced into complex living environments. What is more, mixtures of species, which may be both endogenous and introduced into the sample, may exhibit 1) very similar lifetimes as well as 2) wide ranges of lifetimes including lifetimes shorter than the instrumental response function or whose duration may be long enough to be comparable to the interpulse window. By contrast, existing methods of analysis are optimized for well-separated and intermediate lifetimes. Here, we broaden the applicability of fluorescence lifetime analysis by simultaneously treating unknown mixtures of arbitrary lifetimes-outside the intermediate, Goldilocks, zone-for data drawn from a single confocal spot leveraging the tools of Bayesian nonparametrics (BNP). We benchmark our algorithm, termed BNP lifetime analysis, using a range of synthetic and experimental data. Moreover, we show that the BNP lifetime analysis method can distinguish and deduce lifetimes using photon counts as small as 500.

Microtubules are dynamic polymers that undergo stochastic transitions between growing and shrinking phases. The structural and chemical properties of these phases remain poorly understood. The transition from growth to shrinkage, termed catastrophe, is not a first-order reaction but rather a multistep process whose frequency increases with the growth time: the microtubule ages as the older microtubule tip becomes more unstable. Aging shows that the growing phase is not a single state but comprises several substates of increasing instability. To investigate whether the shrinking phase is also multistate, we characterized the kinetics of microtubule shrinkage following catastrophe using an in vitro reconstitution assay with purified tubulins. We found that the shrinkage speed is highly variable across microtubules and that the shrinkage speed of individual microtubules slows down over time by as much as several fold. The shrinkage slowdown was observed in both fluorescently labeled and unlabeled microtubules as well as in microtubules polymerized from tubulin purified from different species, suggesting that the shrinkage slowdown is a general property of microtubules. These results indicate that microtubule shrinkage, like catastrophe, is time dependent and that the shrinking microtubule tip passes through a succession of states of increasing stability. We hypothesize that the shrinkage slowdown is due to destabilizing events that took place during growth, which led to multistep catastrophe. This suggests that the aging associated with growth is also manifested during shrinkage, with the older, more unstable growing tip being associated with a faster depolymerizing shrinking tip.

Fatty acid-binding proteins (FABPs) are chaperones that facilitate the transport of long-chain fatty acids within the cell and can provide cargo-dependent localization to specific cellular compartments. Understanding the nature of this transport is important because lipid signaling functions are associated with metabolic pathways impacting disease pathologies including cancer, autism, and schizophrenia. FABPs often associate with cell membranes to acquire and deliver their bound cargo as part of transport. We focus on brain FABP (FABP7), which demonstrates localization to the cytoplasm and nucleus, influencing transcription and fatty acid metabolism. We use a combined biophysical-computational approach to elucidate the interaction between FABP7 and model membranes. Specifically, we use multiple experiments to demonstrate that FABP7 can bind oleic acid and docosahexaenoic acid micelles. Data from NMR and multiscale molecular dynamics simulations reveal that the interaction with micelles is through FABP7's portal region residues. Simulations suggest that binding to membranes occurs through the same residues as micelles. Simulations also capture binding events where fatty acids dissociate from the membrane and enter FABP7's binding pocket. Overall, our data shed light on the interactions between FABP7 and OA or DHA micelles and provide insight into the transport of long-chain fatty acids.

Most tumors have abnormal karyotypes, which arise from mistakes during mitotic division of healthy euploid cells and evolve through numerous complex mechanisms. In a recent mouse model with increased chromosome missegregation, chromosome gains dominate over losses both in pretumor and tumor tissues, whereas T-cell lymphomas are characterized by gains of chromosomes 14 and 15. However, the quantitative understanding of clonal selection leading to tumor karyotype evolution remains unknown. Here we show, by introducing a mathematical model based on a concept of a macro-karyotype, that tumor karyotypes can be explained by proliferation-driven evolution of aneuploid cells. In pretumor cells, increased apoptosis and slower proliferation of cells with monosomies lead to predominant chromosome gains over losses. Tumor karyotypes with gain of one chromosome can be explained by karyotype-dependent proliferation, whereas, for those with two chromosomes, an interplay with karyotype-dependent apoptosis is an additional possible pathway. Thus, evolution of tumor-specific karyotypes requires proliferative advantage of specific aneuploid karyotypes.

In computational neuroscience integrate-and-fire models capture the spike generation by a subthreshold dynamics supplemented by a simple fire-and-reset rule; they allow for a numerically efficient and analytically tractable description of stochastic single cell as well as network dynamics. Stochastic spiking is also a prominent feature of Ca2+ signaling which suggests to adopt the integrate-and-fire approach for this fundamental biophysical process. The model introduced here consists of two components describing 1) activity of clusters of inositol-trisphosphate receptor channels and 2) dynamics of the global Ca2+ concentrations in the cytosol. The cluster dynamics is given in terms of a cyclic Markov chain, capturing the puff, i.e., the punctuated release of Ca2+ from intracellular stores. The cytosolic Ca2+ concentration is described by an integrate-and-fire dynamics driven by the puff current. For the cyclic Markov chain we derive expressions for the statistics of the interpuff interval, the single-puff strength and the puff current assuming constant cytosolic Ca2+. The latter condition is often well approximated because cytosolic Ca2+ varies much slower than the cluster activity does. Furthermore, because the detailed two-component model is numerically expensive to simulate and difficult to treat analytically, we develop an analytical framework to approximate the driving puff current of the stochastic cytosolic Ca2+ dynamics by a temporally uncorrelated Gaussian noise. This approximation reduces our two-component system to an integrate-and-fire model with a nonlinear drift function and a multiplicative Gaussian white noise, a model that is known to generate a renewal spike train, i.e., a point process with statistically independent interspike intervals. The model allows for fast numerical simulations, permits to derive analytical expressions for the rate of Ca2+ spiking and the coefficient of variation of the interspike interval, and to approximate the interspike interval density and the spike train power spectrum. Comparison of these statistics to experimental data is discussed.

In biology, release of Ca2+ ions in the cytosol is essential to trigger or control many cell functions. Calcium signaling acutely depends on lipid membrane permeability to Ca2+. For proper understanding of membrane permeability to Ca2+, both membrane hydration and the structure of the hydrophobic core must be taken into account. Here, we vary the hydrophobic core of bilayer membranes and observe different types of behavior in high-throughput wide-field second harmonic imaging. Ca2+ translocation is observed through mono-unsaturated (DOPC:DOPA) membranes, reduced upon the addition of cholesterol, and completely inhibited for branched (DPhPC:DPhPA) and poly-unsaturated (SLPC:SLPA) lipid membranes. We propose, using molecular dynamics simulations, that ion transport occurs through ion-induced transient pores, which requires nonequilibrium membrane restructuring. This results in different rates at different locations and suggests that the hydrophobic structure of lipids plays a much more sophisticated regulating role than previously thought.

Adherent cells use actomyosin contractility to generate mechanical force and to sense the physical properties of their environment, with dramatic consequences for migration, division, differentiation, and fate. However, the organization of the actomyosin system within cells is highly variable, with its assembly and function being controlled by small GTPases from the Rho family. To understand better how activation of these regulators translates into cell-scale force generation in the context of different physical environments, here we combine recent advances in non-neuronal optogenetics with micropatterning and traction force microscopy on soft elastic substrates. We find that, after whole-cell RhoA activation by the CRY2/CIBN optogenetic system with a short pulse of 100 ms, single cells contract on a minute timescale in proportion to their original traction force, before returning to their original tension setpoint with near perfect precision, on a longer timescale of several minutes. To decouple the biochemical and mechanical elements of this response, we introduce a mathematical model that is parametrized by fits to the dynamics of the substrate deformation energy. We find that the RhoA response builds up quickly on a timescale of 20 s, but decays slowly on a timescale of 50 s. The larger the cells and the more polarized their actin cytoskeleton, the more substrate deformation energy is generated. RhoA activation starts to saturate if optogenetic pulse length exceeds 50 ms, revealing the intrinsic limits of biochemical activation. Together our results suggest that adherent cells establish tensional homeostasis by the RhoA system, but that the setpoint and the dynamics around it are strongly determined by cell size and the architecture of the actin cytoskeleton, which both are controlled by the extracellular environment.

We address the challenge of understanding how hydrophobic interactions are encoded by fusion peptide (FP) sequences within coronavirus (CoV) spike proteins. Within the FPs of severe acute respiratory syndrome CoV 2 and Middle East respiratory syndrome CoV (MERS-CoV), a largely conserved peptide sequence called FP1 (SFIEDLLFNK and SAIEDLLFDK in SARS-2 and MERS, respectively) has been proposed to play a key role in encoding hydrophobic interactions that drive viral-host cell membrane fusion. Although a non-polar triad (Leu-Leu-Phe (LLF)) is common to both FP1 sequences, and thought to dominate the encoding of hydrophobic interactions, FP1 from SARS-2 and MERS differ in two residues (Phe 2 versus Ala 2 and Asn 9 versus Asp 9, respectively). Here we explore whether single-molecule force measurements can quantify hydrophobic interactions encoded by FP1 sequences, and then ask whether sequence variations between FP1 from SARS-2 and MERS lead to significant differences in hydrophobic interactions. We find that both SARS-2 and MERS wild-type FP1 generate measurable hydrophobic interactions at the single-molecule level, but that SARS-2 FP1 encodes a substantially stronger hydrophobic interaction than its MERS counterpart (1.91 ± 0.03 nN versus 0.68 ± 0.03 nN, respectively). By performing force measurements with FP1 sequences with single amino acid substitutions, we determine that a single-residue mutation (Phe 2 versus Ala 2) causes the almost threefold difference in the hydrophobic interaction strength generated by the FP1 of SARS-2 versus MERS, despite the presence of LLF in both sequences. Infrared spectroscopy and circular dichroism measurements support the proposal that the outsized influence of Phe 2 versus Ala 2 on the hydrophobic interaction arises from variation in the secondary structure adopted by FP1. Overall, these insights reveal how single-residue diversity in viral FPs, including FP1 of SARS-CoV-2 and MERS-CoV, can lead to substantial changes in intermolecular interactions proposed to play a key role in viral fusion, and hint at strategies for regulating hydrophobic interactions of peptides in a range of contexts.

During clotting under flow, thrombin rapidly generates fibrin, whereas fibrin potently sequesters thrombin. This co-regulation was studied using microfluidic whole blood clotting on collagen/tissue factor, followed by buffer wash, and a start/stop cycling flow assay using the thrombin fluorogenic substrate, Boc-Val-Pro-Arg-AMC. After 3 min of clotting (100 s-1) and 5 min of buffer wash, non-elutable thrombin activity was easily detected during cycles of flow cessation. Non-elutable thrombin was similarly detected in plasma clots or arterial whole blood clots (1000 s-1). This thrombin activity was ablated by Phe-Pro-Arg-chloromethylketone (PPACK), apixaban, or Gly-Pro-Arg-Pro to inhibit fibrin. Reaction-diffusion simulations predicted 108 nM thrombin within the clot. Heparin addition to the start/stop assay had little effect on fibrin-bound thrombin, whereas addition of heparin-antithrombin (AT) required over 6 min to inhibit the thrombin, indicating a substantial diffusion limitation. In contrast, heparin-AT rapidly inhibited thrombin within microfluidic plasma clots, indicating marked differences in fibrin structure and functionality between plasma clots and whole blood clots. Addition of GPVI-Fab to blood before venous or arterial clotting (200 or 1000 s-1) markedly reduced fibrin-bound thrombin, whereas GPVI-Fab addition after 90 s of clotting had no effect. Perfusion of AF647-fibrinogen over washed fluorescein isothiocyanate (FITC)-fibrin clots resulted in an intense red layer around, but not within, the original FITC-fibrin. Similarly, introduction of plasma/AF647-fibrinogen generated substantial red fibrin masses that did not penetrate the original green clots, demonstrating that fibrin cannot be re-clotted with fibrinogen. Overall, thrombin within fibrin is non-elutable, easily accessed by peptides, slowly accessed by average-sized proteins (heparin/AT), and not accessible to fresh fibrinogen.